Definitions: As used herein and in any appended claims, the term “radiometry” shall refer generally to any measurement of the radiance of electromagnetic radiation within a specified spectral band.
“Radiance” is the electromagnetic power emitted per unit area of a surface per unit solid angle and is typically measured in units of W/m2/sr. “Spectral radiance” is the radiance per unit wavelength, given, say, in W/m2/sr/μm.
Radiance is related to the effective temperature of a surface (the product of its temperature and emissivity) in a manner expressed by Planck's law, which, when integrated over all spectral energies, yields the well-known T4-dependence of the Stefan-Boltzmann law. However, measurements over finite spectral energy ranges dictated, say, by band-limited infrared radiation detection, require explicit evaluation of the integral of Planck's law over the band concerned, typically approximated using one of the forms of the Sakuma-Hattori equation, described in Sakuma et al., Establishing a practical temperature standard by using a narrow-band radiation thermometer with a silicon detector, Temperature: Its Measurement and Control in Science and Industry, vol. 5, pp. 421-27 (1982), which is incorporated herein by reference, or by other approximation methods.
An image (as defined below) representing the spatial distribution (in a space of any dimensionality) of surface temperature may be referred to as a “thermogram.” “Thermography,” as used herein and in any appended claims, shall denote the study, by imaging means, of temperature distributions in structures or regions, for example, in buildings.
“Infrared thermography” shall refer to thermography performed in whole, or in part, within the infrared portion of the electromagnetic spectrum, and more particularly, within the so-called “thermal infrared” portion of the spectrum, which need not be precisely defined herein, insofar as the term is used without limitation herein. Long-wave infrared (LWIR) detection [˜8-14 μm] is typically employed for mapping temperatures near typical ambient terrestrial temperatures (˜300° K.), because emittance (radiance integrated over solid angle) is maximized in that range, and because transmission through mist and smoke is considered superior to that of other spectral ranges.
The term “detector” may be used herein comprehensively, and interchangeably with the term “sensor,” with either term applying either to a single detector element or to an array of sensors or detectors, whether sensitive to the flux of impinging photons, or whether sensitive to temperature in radiative equilibrium with a distant source, such as a bolometer. An array of detectors at the focal plane of an optical system may also be referred to, herein, as a camera.
The term “three-dimensional (or 3D) radiometry,” as used herein and in any appended claims, shall refer to radiometry, as previously defined, that takes into account the three-dimensional nature of a scene in order to measure the radiance to infer a derived quantity such as a temperature, associated with a particular surface comprising a portion of the scene.
The term “drive-by thermography,” as used herein and in any appended claims, is defined as the imaging of urban environments by scanning them from a vehicle on the street and the assignment of temperatures to points on the surfaces of the scene.
One class of application of radiometry entails the imaging of radiance over a specified range of the infrared in order to infer surface temperature maps of complex objects. In applications of this sort, anomalous hot spots, or regions of large thermal gradients, are identified in images and related to physical locations on structures in order to identify radiant energy leakage, for example.
Complications in thermography arise because the mapping of detected radiance to surface temperature is not a simple one, especially when the geometry of the emitting surface is complex. At a minimum, a distance to the emitting surface must be known or assumed, and, similarly, an emissivity must be assumed or otherwise ascertained. That is why Cho et al., 3D Thermal Modeling for Existing Buildings using Hybrid LIDAR System, Computing in Civil Engineering, pp. 552-58 (2011), incorporated herein by reference, teaches the concomitant application of a second modality (LIDAR, in that case) in order to associate a distance with distinct points associated with the imaged scene. Similarly, Yang et al., Fusion of camera images and laser scans for wide baseline 3D scene alignment in urban environments, J. Photogram. Remote Sensing (2011), doi:10.1016/j.isprsjprs.2011.09.004, albeit not in a thermographic context, employs information separately derived from a laser scanner in order to build a third dimension into an otherwise two-dimensional image.
Aerial thermography, as applied to urban scenes, for example, by Allinson, Evaluation of aerial thermography to discriminate loft insulation in residential housing, (U. Nottingham, 2007) to the roofs of Nottingham, and by Meier et al., Determination of persistence effects in spatio-temporal patterns of upward long-wave radiation flux density from an urban courtyard by means of time-sequential thermography, Remote Sensing of Environment, pp. 21-34 (2010) to the courtyards of Berlin, suffers from many acknowledged uncertainties, and is, essentially, uncalibrated and uncalibratable. Despite discussion by Schmidt et al., Über die Richtungsverteilung der Wärmestrahlung von Oberflächen. Forschung auf dem Gebiet des Ingenieurwesens A, vol. 6, pp. 175-83 (1935) (hereinafter, Schmidt et al., (1935)), of emissivity variation with viewing angle, the roof pitch (and, thus, sky view factor), and the effects of non-Lambertian emission (variation of emissivity with viewing angle of regard) can only be estimated in the aggregate using current aerial thermography techniques. The techniques of aerial thermography that are known in the art have no bearing on the problem of drive-by thermography, in fact, they are entirely irrelevant to street-level applications.
As practiced, aerial thermography is essentially 2D thermography, where ad hoc corrections are made to account for the failure of the assumptions of 2D radiometry. In particular, the “view factor” F12 as defined between two infinitesimal surface elements, is a geometric function describing the space angle subtended by one differential area dA1 with respect to a second differential area dA2, as well-known and thoroughly covered by Modest, Radiative Heat Transfer (2d ed., 2003), pp. 145-49, for example. Rigorously, the view factor is given by
      F    12    =                    cos        ⁢                                  ⁢                  θ          1                ⁢        cos        ⁢                                  ⁢                  θ          2                            π        ⁢                                  ⁢                  S          2                      ⁢                  ⅆ                  A          2                    .      where θi is the angle between a line connecting differential elements dAi and the normals to the respective elements, and S is the distance between the elements. In 2D radiometry, since one cannot know, or account for, the relative orientation of surfaces, θi are assumed to be identically zero. Thus, for example, the emitting surface is deemed parallel to the sensing plane, and at a fixed distance. Moreover, 2D thermography assumes a constant emissivity for all points on a long wave infrared image.
Previous forays into 3D thermography have adopted one or more of a number of stratagems: they have addressed isolated, static objects (thereby obviating many geometrical complexity issues), or have exploited the inherent stereoscopic characteristic of multiple thermal cameras, or, else, have combined the data of a thermal camera with data of one or more digital visible images in order to infer 3D characteristics of a scene. 3D thermography of isolated and static objects is described by Kapoor et al., Comparison of Techniques for the 3D Modeling and Thermal Analysis, APEGA 2010, pp. 163-173 (2010), and by Shao, Detecting Sources of Heat Loss in Residential Buildings from Infrared Imaging, (MIT Undergraduate Thesis, 2011), both of which are incorporated herein by reference.
It is desirable, however, to provide a mechanism for accurate (real time, nearly real-time, or post processing) analysis of radiometric data obtained in an urban environment on a drive-by basis. The techniques of radiometric analysis, employed to date, however, are far too cumbersome for this purpose, employing either imaging by multiple cameras and/or imaging modalities or explicit distance-measuring modalities, or else invoking averaged calibration factors rather than object- and scene-specific complex geometries. The resolution of the drive-by thermography problem has had to await the novel techniques claimed herein, and described for the first time in the present patent document, and in Phan, Automated Rapid Thermal Imaging Systems Technology, (MIT Ph.D. Dissertation, 2012, unpublished as of the present filing), which is filed herewith as an Appendix, and which is incorporated herein by reference.